Amsterdam - Hybrid (minimum 50% at the office)
€4,900–€5,600 gross per month, based on 40 hours and depending on experience
Futurewhiz is a B Corp
Generative AI can create textbook content in seconds. Producing content that is accurate, curriculum-aligned, editable and trusted by authors and editors—and doing so reliably at scale—is much harder. That is the challenge you will help us solve.
Futurewhiz is looking for a Senior AI Product Engineer to help turn promising AI experiments into dependable software for real publishing workflows. You will remain deeply hands-on while taking broader responsibility for technical direction, architecture and the path from an uncertain opportunity to a durable product.
This is not a role where product decisions arrive as fully specified tickets. You will work with editorial and technical colleagues to frame problems, test assumptions and decide what is worth building. Seniority here means sound judgement, independent ownership and the ability to make the wider team more effective—not status, people management or knowing every technology in advance.
For nearly 15 years, Futurewhiz has been the market leader in EdTech in the Netherlands. Our brands – including Squla and StudyGo – help children and teenagers aged 3 to 18 learn and grow at their own level and pace. Our mission is clear: "Empowering every child to grow." We’ve been a certified B Corp since 2020, which means we strive for a strong balance between purpose and profit.
You will join the Futurewhiz Content Automation team and work closely with software engineers, editorial specialists and colleagues at a major educational publisher. Together, you will improve the workflows used to create and maintain high-quality learning materials, including textbooks and digital content.
Each cross-functional team focuses on a particular part of the publishing workflow. The team studies where time, quality or cost is being lost; tests possible improvements with users; and builds the solutions that show the most promise. Once the best opportunities in one area have been addressed, the team may move to another part of the workflow.
Your editorial colleague will lead much of the specialist research, such as interviewing authors and editors, testing editorial concepts and mapping publishing workflows. You will participate where technical insight, feasibility testing or rapid prototyping is valuable, while owning the technical approach and ensuring the resulting software can succeed beyond the prototype stage.
Specifically, you will:
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Own the technical direction for an AI-assisted product area from early discovery through production operation
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Build across the stack: Python services and APIs, data flows, user-facing interfaces and the infrastructure needed to run them
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Design robust LLM and agent-based workflows, including prompts, evaluations, feedback loops, observability and safeguards
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Translate editorial research and user feedback into technical options, trade-offs and testable plans
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Identify the smallest useful experiments that can resolve important technical or product uncertainty
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Create architectures that support rapid learning now without preventing the strongest ideas from becoming durable products
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Develop reusable platform capabilities and integration patterns that can support multiple content workflows
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Set pragmatic standards for reliability, security, maintainability, quality and cost—and help the team apply them
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Use AI coding tools fluently while critically reviewing their output and remaining accountable for the software you ship
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Anticipate dependencies, investigate difficult failures across components and keep production systems effective as usage grows
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Raise the engineering bar through design discussions, code reviews, pairing and informal mentoring
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Navigate technical trade-offs with both technical and non-technical stakeholders, including when priorities or perspectives differ
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Travel to Groningen for one or two days approximately once every two months to work with colleagues there
There is no separate team waiting to take over UX, infrastructure or operations. You will have colleagues to consult, but the product team owns its solutions end to end. Part of your role is helping the team keep that ownership manageable through simple architecture and good engineering choices.
In your first three months, we would expect you to:
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Build a strong understanding of the users, workflow, technical environment and existing experiments in your initial problem area
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Establish a clear technical direction based on the most important evidence and uncertainties
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Ship and evaluate a useful prototype or production improvement with real users
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Take end-to-end ownership of a meaningful product area, including its architecture, deployment and operation
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Build trust with technical, editorial and publishing stakeholders
As you become established, success means independently moving the team from uncertain opportunities to tested solutions and turning the strongest ideas into dependable software. The clearest measure of your work will be whether the systems you help create generate high-quality educational content consistently while improving speed, cost or editorial effort. You will also leave the wider platform and engineering team better equipped for the next workflow we tackle.
You are a product-minded engineer who combines technical breadth with practical judgement. You can move quickly when learning, slow down when reliability matters and distinguish between an experiment that should remain simple and a capability worth building for the long term.
You are likely to thrive here if you:
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Have a track record of independently building, shipping and operating production software
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Are strong in Python and comfortable making effective decisions across backend, frontend and infrastructure concerns
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Have practical experience with LLM-powered products, model APIs, agent workflows or closely related AI systems
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Use AI tools as a normal part of your engineering practice to explore, build and learn faster, while verifying their work critically
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Can frame ambiguous problems, identify the riskiest assumptions and turn them into focused experiments
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Make architecture decisions that balance immediate product learning with reliability and future reuse
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Take responsibility for outcomes across the full lifecycle rather than stopping when the code is merged
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Communicate complex choices clearly to non-technical colleagues and incorporate their domain expertise into the solution
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Can guide other engineers through collaboration, review and mentoring without needing a formal management role
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Remain pragmatic and constructive under pressure or when stakeholders hold competing views
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Have an affinity for education and want your work to improve how learning materials are made
Experience with React or TypeScript, cloud infrastructure, containers, CI/CD, LLM evaluation, data analysis or applied machine learning would be valuable. Experience in education, publishing or content systems is welcome but not required.
We are not looking for a particular pedigree or an engineer who already knows everything. We are looking for someone whose experience enables good independent decisions, who remains curious and who has genuinely adapted their way of working to the possibilities and limitations of modern AI.
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A gross monthly salary of €4,900–€5,600, based on 40 hours and depending on experience
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24 vacation days + 3 assigned days off + 1 skipping school day
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Collective pension and health insurance
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A €600 annual learning budget for your professional development
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Unlimited access to external coaches through Inuka Coaching
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Unlimited access to Goodhabitz training programs for professional and personal growth
Additionally:
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Lifetime access to StudyGo and Squla accounts
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Office next to Bijlmer Arena station (with the possibility of getting a Swapfiets or an OV business card if you live over 7km from the office)
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A MacBook for work
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Payroll Giving option to contribute to a good cause
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Healthy lunches at the office, unlimited good coffee, fresh fruit, and snacks
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A Culture Crew that organizes fun activities like outings, pub quizzes, ski trips, and laser tag
We are a passionate and diverse team united by a shared mission: helping children thrive in their learning journey and empowering them to grow through personalised education.
Our culture is welcoming and authentic. We believe people do their best work when they can be themselves, and we actively value different backgrounds, ideas, experiences and perspectives. This diversity helps us serve young learners more effectively, regardless of who they are.
Our platforms are for everyone, and the same applies to our workplace. Everyone is welcome on this journey.
At Futurewhiz, AI is not a side project. We use it throughout our work to move faster, explore more possibilities and improve the support we provide to children, parents, teachers, authors and editors.
For this role, being AI-native means more than using ChatGPT occasionally. It means knowing how to collaborate effectively with AI tools, verify their output, protect sensitive information and remain accountable for the quality of what you ship.
Do you have any questions about AI and our use of it in the recruitment process? Send us a message to [email protected]
We would love to hear from you even if you do not check every box. If the challenge excites you and you have evidence that you can turn ambiguous ideas into useful, dependable products, be yourself and go for it.
Upload your CV and a short motivation through the application button. In your motivation, we would especially like to hear about one product or platform capability you helped take from uncertainty to production: what problem it addressed, what you personally owned, which trade-offs you made and how you knew it was successful.
Applicants must already have the right to work in the Netherlands. We are unable to provide visa sponsorship or relocation support for this vacancy.
